Venkateshbabu Nagendrababu1, Anita Aminoshariae2, Jim Kulild3. 1. Department of Preventive and Restorative Dentistry, College of Dental Medicine, University of Sharjah, Sharjah, UAE. 2. Department of Endodontics, Case School of Dental Medicine, Cleveland, Ohio, USA. Electronic address: Axa53@case.edu. 3. Department of Endodontics, UMKC School of Dentistry, Kansas City, MO, USA.
Abstract
INTRODUCTION: Artificial intelligence (AI) has the potential to replicate human intelligence to perform prediction and complex decision making in healthcare and has significantly increased its presence and relevance in various tasks and applications in dentistry, especially Endodontics. The aim of this review was to discuss the current Endodontic applications of AI and potential future directions. METHODS: Articles that have addressed the applications of AI in Endodontics were evaluated for information pertinent to include in this narrative review. RESULTS: AI models, e.g. convolutional neural networks and/or artificial neural networks, have demonstrated various applications in Endodontics such as studying root canal system anatomy, detecting periapical lesions and root fractures, determining working length measurements, predicting the viability of dental pulp stem cells and predicting success of retreatment procedures. The future of this technology was discussed in light of helping with scheduling, treating patients, drug-drug interactions, diagnosis with prognostic values, and robotic-assisted endodontic surgery. CONCLUSION: AI demonstrated accuracy and precision in terms of detection, determination and disease prediction in Endodontics. AI can contribute to improvement of diagnosis and treatment that can lead to an increase in the success of Endodontic treatment outcomes. However, it is still necessary to further verify the reliability, applicability and cost-effectiveness of AI models prior to transferring these models into day-to-day clinical practice.
INTRODUCTION: Artificial intelligence (AI) has the potential to replicate human intelligence to perform prediction and complex decision making in healthcare and has significantly increased its presence and relevance in various tasks and applications in dentistry, especially Endodontics. The aim of this review was to discuss the current Endodontic applications of AI and potential future directions. METHODS: Articles that have addressed the applications of AI in Endodontics were evaluated for information pertinent to include in this narrative review. RESULTS: AI models, e.g. convolutional neural networks and/or artificial neural networks, have demonstrated various applications in Endodontics such as studying root canal system anatomy, detecting periapical lesions and root fractures, determining working length measurements, predicting the viability of dental pulp stem cells and predicting success of retreatment procedures. The future of this technology was discussed in light of helping with scheduling, treating patients, drug-drug interactions, diagnosis with prognostic values, and robotic-assisted endodontic surgery. CONCLUSION: AI demonstrated accuracy and precision in terms of detection, determination and disease prediction in Endodontics. AI can contribute to improvement of diagnosis and treatment that can lead to an increase in the success of Endodontic treatment outcomes. However, it is still necessary to further verify the reliability, applicability and cost-effectiveness of AI models prior to transferring these models into day-to-day clinical practice.
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